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Strain improvement, artificial intelligence optimization, and sensitivity analysis of asparaginase-mediated acrylamide reduction in sweet potato chips

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Abstract

In recent times, L-asparaginase has emerged as a potential anti-carcinogen through hydrolysis of L-asparagine in the blood for anti-leukemic application, and in carbohydrate-based foods, for acrylamide reduction applications. In this study, Aspergillus sydowii strain UCCM 00124 produced an L-asparaginase with a baseline acrylamide reduction potential of 64.5% in sweet potato chips. Plasma mutagenesis at atmospheric pressure and room temperature (ARTP) was employed to improve L-asparaginase production while artificial neural network embedded with genetic algorithm (ANN-GA) and global sensitivity analysis were used to identify and optimize process conditions for improved acrylamide reduction in sweet potato chips. The ARTP mutagenesis generated a valine-deficient mutant, Val-Asp-S-180-L with 2.5-fold L-asparaginase improvement. The ANN-GA hybrid evolutionary intelligence significantly improved process efficiency to 98.18% under optimized conditions set as 118.6 °C, 726.37 g/L asparagine content, 9.92 µg/mL L-asparaginase, 4.54% NaCl, and soaking time of 15 h without significant changes in sensory properties. The sensitivity index revealed initial asparagine content as the most sensitive parameter to the bioprocess. The enzyme demonstrated significant thermo-stability with Arrhenius deactivation rate constant, Kd, of 0.00562 min−1 and half-life, t1/2, of 123.35 min at 338 K. These conditions are recommended for sustainable healthier, and safer sweet potato chips processing in the food industry.

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Data generated in this study are provided in the main manuscript and Supplementary material. Additional data may be provided upon reasonable request by the corresponding author.

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Acknowledgements

Authors are grateful to personnel at Sheda Facility, Abuja, Central laboratory, University of Ibadan, Nigeria and Food Science and Technology laboratory, University of Calabar, Nigeria and University of Calabar Collection of Microorganisms, for technical assistance.

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The submitted work did not receive funding from any government or non-government sources.

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Contributions

ME conceived the idea; EA, DU, EI conducted the experiments while ME and AA supervised the work; ME, AAm, HK analyzed data; ME, AA, AAm prepared original draft; HK and SA edited the final manuscript. All authors read approved the final manuscript.

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Correspondence to Maurice Ekpenyong.

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The authors declare that they have no competing interests.

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The participant at the sensory evaluation of L-asparaginase treated sweet potato fries freely and willingly consented to participate but opted to remain anonymous.

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Akwagiobe, E., Ekpenyong, M., Asitok, A. et al. Strain improvement, artificial intelligence optimization, and sensitivity analysis of asparaginase-mediated acrylamide reduction in sweet potato chips. J Food Sci Technol 60, 2358–2369 (2023). https://doi.org/10.1007/s13197-023-05757-5

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  • DOI: https://doi.org/10.1007/s13197-023-05757-5

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